Enhanced automotive passive entry

ABSTRACT

Methods and devices are provided for allowing a mobile device (e.g., a key fob or a consumer electronic device, such as a mobile phone, watch, or other wearable device) to interact with a vehicle such that a location of the mobile device can be determined by the vehicle, thereby enabling certain functionality of the vehicle. A device may include both RF antenna(s) and magnetic antenna(s) for determining a location of a mobile device relative to the vehicle. Such a hybrid approach can provide various advantages. Existing magnetic coils on a mobile device (e.g., for charging or communication) may be re-used for distance measurements that are supplemented by the RF measurements. Any device antenna may provide measurements to a machine learning model that determines a region in which the mobile device resides, based on training measurements in the regions.

CROSS-REFERENCES TO RELATED APPLICATIONS

This application is a continuation of U.S. Non-Provisional applicationSer. No. 16/371,838, entitled “Enhanced Automotive Passive Entry” filedApr. 1, 2019, which is a continuation of U.S. Non-Provisionalapplication Ser. No. 15/894,774, entitled “Enhanced Automotive PassiveEntry” filed Feb. 12, 2018, now U.S. Pat. No. 10,285,013, which claimspriority to U.S. Provisional Application No. 62/457,747, entitled“Enhanced Automotive Passive Entry” filed Feb. 10, 2017, the entirecontents of which are herein incorporated by reference for all purposes.

BACKGROUND

Modern cars allow entry using a key fob, and some cars allow starting bya button when the key fob is inside the car. Such operation is calledpassive entry and passive start, which use a position of the key fob tounlock the car, allow starting the car, and provide other functionality.The location of the key fob is determined using magnetic signals emittedfrom magnetic antennas in the car. The magnetic signals are measured bythe key fob and sent to the car for determining a location of the keyfob.

The key fob can be bulky and be an additional item that a user mustcarry. Further, the magnetic fields are short range, and currenttechniques are susceptible to hackers, which can allow a thief to accessthe car and potentially steal it.

Therefore, it is desirable to provide new methods and devices thatovercome any one of these problems.

BRIEF SUMMARY

Some embodiments can provide methods and devices for allowing a mobiledevice (e.g., a key fob or a consumer electronic device, such as amobile phone, watch, or other wearable device) to interact with avehicle such that a location of the mobile device can be determined bythe vehicle, thereby enabling certain functionality of the vehicle.

According to one embodiment, the mobile device and the vehicle caninclude radiofrequency (RF) antenna(s) and magnetic antenna(s). Themobile device can measure signal properties of the RF signals and themagnetic signals from the vehicle that relate to a distance of thedevice's antenna from a vehicle antenna. Examples of signal propertiesinclude a received signal strength indicator (RSSI) and a time-of-flightvalue (e.g., a round trip time, RTT). In some implementations, themagnetic antenna(s) can measure an RSSI of the magnetic signals, and theRF antenna(s) can measure a time-of-flight value. The various types ofantennas can be used in combination or separately. For example, the RFantenna(s) can be used to determine changes in location of the mobiledevice far from the vehicle (e.g., to determine a user is approachingthe vehicle), while the magnetic antenna(s) can be used to determine alocation of the mobile device when the mobile device is near or insidethe vehicle. Either the mobile device or the vehicle can determine thelocation. The location can be provided to a control unit of the vehicle,thereby enabling the control unit to perform a prescribed operation ofthe vehicle, such as unlocking one or more doors or allowing use of astart button.

In some embodiments, magnetic charging coils can be reused as a magneticantenna. In other embodiments, a near-field communications (NFC) antennacan be reused as a magnetic antenna for use in determining a location ofthe device. Such a reuse of one or both can avoid a need for dedicatedmagnetic antennas and providing for a smaller and less expensive mobiledevice. In other implementations, a vehicle can have three-dimensionalmagnetic antennas, thereby allowing the mobile device to have only onemagnetic antenna.

According to another embodiment, signal values measured from one or moreantennas (e.g., RF or magnetic) can be used with a machine learningmodel to classify a location of the mobile device as being within one ofa set of regions. The set of regions can include a first subset of oneor more regions outside the vehicle and a second subset of one or moreregions outside the vehicle. The machine learning model can be trainedusing various sets of signal values measured at locations across theplurality of regions. The particular region can be provided to a controlunit of the vehicle, thereby enabling the control unit to perform aprescribed operation of the vehicle.

A better understanding of the nature and advantages of embodiments ofthe present invention may be gained with reference to the followingdetailed description and the accompanying drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows a vehicle with an LF location system.

FIG. 2 shows the internals of a key fob.

FIG. 3 shows the high-level system design for an LF passiveentry/passive start automotive system.

FIG. 4 shows an alternative high-level system design for an RF rangingpassive entry/passive start automotive system according to embodimentsof the present invention.

FIG. 5 shows a sequence diagram of a ranging operation involving amobile device and three antennas of a vehicle according to embodimentsof the present invention.

FIG. 6 shows a proposed high-level system design for a hybrid LFmagnetic+RF ranging system for passive entry/passive start automotivesystem according to embodiments of the present invention.

FIG. 7 shows a mobile device having components for data collection,processing, and transfer of measurements and ancillary data according toembodiments of the present invention.

FIG. 8 is a flowchart of method of enabling an operation by a vehicleinvolving a mobile device according to embodiments of the presentinvention.

FIG. 9 shows a region-based passive entry/passive start automotivesystem according to embodiments of the present invention.

FIG. 10 shows a proposed machine learning training processing diagramaccording to embodiments of the present invention.

FIG. 11 shows an implementation of the machine-learning model foridentifying which region a mobile device is located relative to avehicle according to embodiments of the present invention.

FIG. 12 is a flowchart of a method for enabling an operation by avehicle involving a mobile device.

FIG. 13 is a block diagram of an example device, which may be a mobiledevice, in accordance with some embodiments.

DETAILED DESCRIPTION

Some embodiments can enable a consumer electronic device (e.g., a mobilephone, watch, or other wearable device) to unlock and/or start anautomobile without the need for a dedicated automotive key fob. Consumerelectronic devices do not have the available physical space for atypical key fob, including three low-frequency (LF) magnetic antennas.Embodiments can implement a hybrid location solution that uses one ormore RF antennas and one or more magnetic antennas. Such animplementation can still provide 10-cm location accuracy, therebyenabling a passive entry/passive start solution in automobiles.

Some embodiment can fewer than three magnetic antennas and/or smallermagnetic antennas, in order to provide the desired functionality andaccuracy. In one embodiment, magnetic charging coils can be reused as amagnetic antenna. In another embodiment, a near-field communications(NFC) antenna can be reused as a magnetic antenna for use in determininga location of the device. Such a reuse of one or both can avoid a needfor dedicated magnetic antennas and providing for a smaller and lessexpensive mobile device.

Some embodiments can enable a mobile device (e.g., a key fob or mobilephone) to unlock and start an automobile using a machine learning modelthat determines whether a mobile device is in one of a set of regions(e.g., a set of predetermined regions) in and around a vehicle. Themachine learning model can enable passive entry/passive start in thepresence of signal attenuation, delay, and multipath, thereby enablingentry in automobiles without the need for LF antennas and LF signals. Insome implementations, LF antennas may be used to improve accuracy.

I. Passive Entry Using LF

Automotive key fobs with passive entry/passive start capabilities uselow-frequency (LF) magnetic signals to determine location of the keyfob. This technology can enable 10-cm location accuracy. This accuracyis needed for feature reliability and can be a requirement of insurancecompanies. LF-based key fobs have relatively large antennas and aresusceptible to man-in-the-middle attacks.

A. Operations

FIG. 1 shows a vehicle 100 with an LF location system. In automobiles,an LF magnetic system is used to locate a key fob 105. Per FIG. 1 ,modern automobiles typically have multiple transmitting LF magneticantennas 110 (e.g., 4-8). These antennas are 1-dimensional, in that thevector magnetic field they generate is primarily in one direction. Theyare placed throughout a car in order to provide good geometricalaccuracy when localizing the key fob. The 1-D magnetic field generatedby the automotive LF antennas is compensated for by the 3-D LF antennain the key fob, which can measure at the vector magnetic field strength.

RF receiver 120 can receive measurement data from key fob 105 andcommunicate the measurements to a vehicle control unit 130, which cancontrol door sensors 140 a start/stop button 150. As shown, vehiclecontrol unit 130 is connected to motor control unit 160, which operatesthe motive function of the automobile. As mentioned above, key fob 105is typically bulky and an extra device that needs to be carried.

A limp-home antenna 170 can that key fob 105 has been removed, therebyinitiating a limp-home mode for vehicle 100. A limp-home mode canpartially disable the vehicle, while maintaining the ability to drive.One example is when the key fob is present inside of a vehicle to startthe vehicle, and then the key fob is removed from the interior of thevehicle (e.g., lost or thrown out the window). In this case, the vehiclemay indicate the key fob is missing but may continue to allow the engineto run and the vehicle to be driven. In this example, the vehicle cannotbe restarted without bringing the key fob back into the interior of thevehicle.

B. LF Device

Existing automotive passive entry/passive start systems work by usinglow-frequency (LF) magnetic signals (e.g., at 100s of kHz, such as up to500, 600, 700, 800, or 900 kHz) to localize a key fob. The locationprovides the necessary input to determine what action the automobileshould take. Some examples of decisions based on key fob location arewhether or not to: unlock doors, start the car, or prevent rear hatchfrom closing with key inside.

Existing LF technology requires an antenna with a relatively largevolume, thereby requiring a large key fob or making it challenging tointegrate into a consumer mobile device, e.g., smartphone or watch. Forexample, a consumer mobile/electronic device typically has a displayscreen (e.g., a touchscreen) and ideally has a thin, flat shape, whichis difficult to maintain if a standard 3D LF antenna was added. Anotherchallenge is that there are man-in-the-middle attacks on the LF signaldue to its slow modulation rate. These attacks, if successful, can allowsomeone to steal an automobile.

FIG. 2 shows the internals of a key fob 200. FIG. 2 illustrates therelatively large size of the three LF antennas 205 (providing 3orthogonal measurements of the vector field) required for 10-cmlocalization accuracy. As shown, the antenna 210 has a diameter of about2 cm. 10-cm localization accuracy is required to meet insurancerequirements and needed for reliable passive entry/passive start. The3D-antenna can ensure that a sufficiently strong signal is measured bythe key fob, regardless of its orientation. For example, the vehiclemagnetic antennas are typically a solenoid coil with a magnet inside thesolenoid, which provides a mostly linear magnetic field. If the device'scoil is not oriented to have an axis in at least some alignment (e.g.,parallel with) with the linear magnetic field from the vehicle antenna,the magnetic flux measured in the device coils can diminish. Havingthree coils that are orthogonal with each other can ensure that at leastone of the coils is receiving a strong signal. Also, when the signalstrengths from the three coils are combined, the total is generallyinvariant with respect to orientation.

C. Location Determination

FIG. 3 shows the high-level system design for an LF passiveentry/passive start automotive system. The user physically interactswith the automobile, e.g., by touching the driver-side door handle orpressing the start button of the automobile. Typically, such a physicalinteraction with the automobile is needed for the automobile to initiala key fob localization using the LF system. Some embodiments describedlater can begin localization based on a communication trigger between adevice and the automobile.

Key fob distance measurements can be made by sequentially orsimultaneously measuring received signal strength from each automotiveLF antenna (antennas 301-304 in FIG. 3 ). A distance measurement is madeby having the key fob measure the received LF field strength from eachantenna and then converting the strength to a distance (laterembodiments described how signal strength can be converted directly to aregion determined, e.g., inside or outside). Specifically, the voltageacross the LF coil is converted into a distance measurement. The powerof the magnetic field strength falls off by 1/r³ in the near field,thereby providing excellent sensitivity to changes in distance. Themeasured magnetic field strength can be correctly associated with eachantenna, thereby allowing triangulation with known positions of LFantennas 301-304. In some embodiments described later, the distance isnot computed, and the signal strength values can be used directly todetermine the key fob location.

The measured LF field strengths (or distances) can then then transmittedback to the automobile in order for the automobile to compute thelocation of the key fob. Alternatively, the key fob could compute thelocation instead or in addition to the automobile determining thelocation. A secondary channel (e.g., a UHF channel) can be used totransfer this information.

In addition to these communications, other communications cancryptographically authenticate the key fob to the automobile andautomobile to the key fob, e.g., using Bluetooth®. Such a securitysystem can have some weakness, primarily from man-in-the-middle attackson the LF sub-system. For example, an attacker can amplify a signal fromthe key fob, which can simulate as if the key fob was near or inside thevehicle. As another example, an attacker can sniff out and save rollingauthentication codes that get re-used. The use of a consumer electronicdevice can enable more advanced authentication techniques.

II. RF Ranging

Some embodiments can provide an improved user experience of a passiveentry/passive start system by removing the need for a key fob entirelyand allow the user's mobile device (e.g., smart phone) to carry out theexisting passive entry/passive start features. As part of enabling amobile device (e.g., a mobile phone) to perform such passivefunctionality, radiofrequency (RF) signals can be used, as opposed tothe low frequency (LF) magnetic signals.

Accordingly, a solution to above problems is to replace (or supplement)the LF subsystem in the automobile and key fob with a high-precision RFranging system integrated into the automobile and mobile device. An RFranging system, such as ultra-wideband (UWB), has cm-level rangingaccuracy, a small antenna suitable for integration into a mobile device,functions substantially far from the automotive (˜10 m away), anddoesn't have the same security vulnerabilities as an LF system.

Another improvement to user experience can be to detect the user'sintent when approaching or leaving the automobile, e.g., the userapproaching the automobile likely has the intent to unlock the vehicleif the vehicle is currently locked. Additionally, as the user approachesthe automobile, the automobile can turn on the interior lights, enablethe heating system, and unlock the doors or trunk, without requiringphysical interaction and doing so securely. Such longer range intent canbe achieved as the power of RF signals decays as 1/r². Anotherimprovement can be to reduce the susceptibility of an LF magneticman-in-the-middle attack.

A. Example RF System

FIG. 4 shows an alternative high-level system design for an RF rangingpassive entry/passive start automotive system according to embodimentsof the present invention. A vehicle 420 can include multiple RF antennas401-403 (3 as shown) that send signals to a mobile device 410. Themobile device 410 can determine a distance from the RF antennas 401-403by use of a signal property, such as RSSI or time-of-flight information(e.g., RTT or just time for one-way transmission). The measured signalvalues can be used by the mobile device 410 or the vehicle 420 (e.g.,after receiving the measured signal values from the mobile device 410)to determine the relative location of the mobile device 410 with respectto the vehicle 420.

Unlike a magnetic LF system, a concern with any RF ranging system isthat the automotive body, nearby obstructions (cars, buildings, ground),and the human body may cause signal multipath and signal attenuation.Multipath and attenuation can degrade the position accuracy of theuser's device such that it may not perform at the required levels forthe automotive industry (e.g., 10-cm accuracy for inside/outsidedetection). For example, the car should be enabled only when the user isin the driver's seat. Multipath can be particularly problematic when theuser is in or near the automobile. To address such issues, someembodiments can use an LF system in combination with the RF system. Inaddition or alternatively, embodiments can use a machine learning modelto determine whether the mobile device is in certain regions in oraround the vehicle. Further, multiple RF antenna may be used in case oneof the antennas is obscured, e.g., by a user's hand.

B. Example RF Ranging Sequence

The mobile device and the vehicle can be paired using a first wirelessprotocol (e.g., Bluetooth®). The mobile device and the vehicle may thencommunicate with each other, e.g., at any time later, including hours,days, weeks, etc. later. After pairing, the vehicle and/or the mobiledevice can be authenticated using the first wireless protocol.

The pairing can occur as a result of the mobile device transmitting anadvertisement signal (e.g., using Bluetooth® low energy (BTLE)), and thevehicle detecting the advertisement signal during a scan. Suchadvertisement and detection can comprise a triggering event to beginlocalization, which can occur farther away than a physical triggering,such as lifting a door handle. Another example of a triggering event isestablishing a BTLE connection, e.g., authenticating the vehicle and/orgenerating keys for ranging. Such keys for authentication can be storedand managed by a secure element, e.g., in an application processor. Themobile device and the vehicle can exchange ranging capabilities usingthe first wireless protocol. Ranging can be initiated using the firstwireless protocol, and then carried out using a second protocol, e.g.,ultra-wideband (UWB). Further details can be found in U.S. ProvisionalNo. 62/565,637, which is incorporated by reference in its entirety. Inother embodiments, a same protocol can be used for authentication andranging.

After the initiation signals using the first wireless protocol, thevehicle can begin scanning for ranging signals at a specified time usingone or more vehicle antenna units corresponding to the second wirelessprotocol. The one or more vehicle antenna units can receive one or moreranging request messages and send one or more ranging response messages.A control unit in each of the one or more vehicle antenna units orshared among them can perform various levels of processing of suchranging messages, e.g., to determine time stamps. The mobile device canreceive the ranging response messages and determine time stamps for thetransmission of the one or more ranging request messages and time stampsfor the one or more ranging response messages. The mobile device cansend these time stamps to the vehicle for determining a distance betweenthe mobile device and the vehicle. In other implementations, the mobiledevice can determine the distance based on transmission and receptiontime of ranging signals. The ranging can continue until a stop rangingrequest is processed. In some embodiments, other location informationbesides distance can be used, e.g., which region the mobile device isin, as described in section IV.

As part of the ranging, the mobile device or vehicle can send an initialranging message, which can include a series of pulses. These pulses canbe narrower than the pulses used in a first wireless protocol used forauthentication. For example, the mobile device can broadcast the initialranging message so that each of the RF antennas of the vehicle canreceive it. The mobile device can track the exact time (e.g., to 10-100picosecond accuracy) at which the initial ranging message was sent. Eachof the vehicle RF antennas can send a ranging response message, whichcan include an identifier that identifies which vehicle RF antenna senta particular response message. The mobile device can track the exacttimes for receiving the ranging response messages.

In some embodiments, the mobile device can send the received times tothe vehicle, which may use its own received times of receiving theinitial ranging message at each of the vehicle RF antennas and the timesof sending each of the three ranging response messages for the exampleof FIG. 4 to determine the distance (or other location information)between the mobile device and the vehicle. Differences in the times ofsending and receiving each of the messages can be used to determine thedistance, e.g., when the clocks of the two devices are synchronized. Asanother example, a time delay of receiving the initial ranging responsemessage and sending a ranging response message can be subtracted fromthe sending and receiving times at the mobile device to obtain the roundtrip time, which can be translated to a distance based on the speed ofthe electromagnetic signal. The known positions of the different RFantennas in the vehicle can be used to triangulate the position of themobile device with respect to vehicle.

In other embodiments, the mobile device can determine the distance (orother location information) from the vehicle. For example, if theranging information exchanged by the vehicle includes (1) relativepositions of the RF antennas of the vehicle and (2) an expected delaybetween receiving a ranging request message and transmitting a rangingresponse message, the mobile device can determine the distance using thereceived times of it sending and receiving ranging messages.

FIG. 5 shows a sequence diagram of a ranging operation involving amobile device 500 and three antennas 552-556 of a vehicle according toembodiments of the present invention. In this example of FIG. 5 , mobiledevice 500 broadcasts a single packet that is received by antennas552-556 (e.g., each of a different node). In another implementation,mobile device 500 can send a packet to each node, and have each noderespond to that distinct packet. The vehicle can listen at a specifiedantenna so that both devices know which vehicle antenna is involved, ora packet can indicate which antenna a message is for. For example, afirst antenna can respond to a received packet; and once the response isreceived, another packet can be sent to a different antenna. But, thisalternative procedure takes more time and power.

FIG. 5 shows a ranging request 510 sent at T1 and being received atantennas 552-556 at times T2, T3, and T4, respectively. Thus, theantennas (e.g., UWB antennas) listen at substantially the same time andrespond independently. Antennas 552-556 provide ranging responses 520,which are sent at times T5, T6, and T7, respectively. Mobile device 500receives the ranging responses at times T8, T9, and T10, respectively.An optional ranging message 530 can be sent (shown at T11) that isreceived by antennas 552-556 at times T12, T13, and T14, respectively.Information 540 (e.g., location, distance, or time) can be sent after aset of ranging messages and may only need to be received by one antenna,which can relay the information to a control unit. In the example shown,time stamps tracked by mobile device 500 are sent to at least one ofantennas 552-556, so that the vehicle can determine the distance fromthe vehicle, e.g., based on the locations of the antennas in thevehicle. In other examples, mobile device 500 can determine a distanceand send the distance to the vehicle. Other location information can bedetermined besides distance, e.g., which region the mobile deviceresides, as described in section IV.

In some embodiments, to determine which ranging response is from whichantenna, the vehicle can inform the mobile device of the order ofresponse messages that are to be sent, e.g., during the ranging setuphandshake. In other embodiments, the ranging responses can includeidentifiers, which indicate which antenna sent the message. Theseidentifiers can be negotiated in the ranging setup handshake.

Use of ranging message 530 can allow improved accuracy. The antennas canbe on a synchronized clock with each other, but the response times(e.g., delay between T2 and T5) can have different delays, e.g., T5-T2and T6-T3 can be different. Ranging message 530 can provide resilienceto the turnaround times being different for each of the antenna nodes.Such differences in turnaround times can result in ranging errors of ameter or two meters. By adding ranging message 530, embodiments canreduce an error due to the different turnaround times. Such an alternateformulation of the distance equation can provide a function of thetimestamps that substantially minimizes the effects of the residualclock drift rates and clock offsets accumulated during the potentiallydifferent turnaround times.

Messages 510-530 can include very little data in the payload, e.g., byincluding fewer pulses than might otherwise be used. Using fewer pulsescan be advantageous. The environment of a vehicle and a mobile device(potentially in a pocket) can make measurements difficult. As anotherexample, a vehicle antenna might face a different direction than thedirection from which the mobile device is approaching. Thus, it isdesirable to use high lower for each pulse, but there are governmentrestrictions (as well as battery concerns) on how much power can be usedwithin a specified time window (e.g., averaged over 1 millisecond). Thepacket frames in these messages can be on the order of 150 to 180microseconds long. The packet frame in a message including information540 can be longer, e.g., 200 or 250 microseconds long.

III. Combined RF and LF

One problem of using LF in a consumer electronic device is a size of themagnetic coils. Specifically, the use of three orthogonal coils toensure an accurate measurement, i.e., that sufficient magnetic flux ismeasured regardless of the orientation of the device. As mentionedabove, an RF-only ranging system may suffer attenuation problems,thereby inhibiting the desired accuracy (e.g., within 10 cm).

Using both RF and LF antennas can reduce such problems. For example,only one LF antenna may be used, as the RF antenna(s) can supplement themeasurements to ensure a sufficiently strong signal from a sufficientnumber of antennas. For instance, the device may not measure asufficiently strong signal from one LF antenna due to a currentorientation of the device, and thus that LF antenna may not provide anyusable location information. But, one or more RF antennas (which may benear the currently unusable LF antenna) may provide a sufficientlystrong signal such that a distance measurement can be made from those RFantennas, thereby supplementing the deficiency caused by the currentorientation of the device. Another implementation could use at least onesmaller magnetic coil than is typically used in existing key fobs (e.g.,a smaller diameter for a coil having windings not in the predominantplane of the display screen of the device).

Additionally, using both RF and LF can reduce the number of RF antennasrelative to an embodiment where the device only uses RF antennas. Thesupplement of the LF antennas (which may be kept for legacy compliance)may reduce the costs of the RF system.

A. Hybrid System

FIG. 6 shows a proposed high-level system design for a hybrid LFmagnetic and RF ranging system for passive entry/passive startautomotive system according to embodiments of the present invention. Thehybrid system can re-use existing LF antennas 601-604 in a vehicle 620,with the possibility of adding one or more LF antennas to provideorthogonal magnetic fields. As shown, the system includes theintegration of RF antennas 651-653 (and potentially ranging chips) invarious locations in vehicle 620. A mobile device 610 can integrate anRF ranging chip and an RF antenna, e.g., as described in FIG. 7 .

Thus, in order to alleviate possible deficiencies that may occur with anRF-only ranging system, a hybrid LF+RF ranging system can be used. Thehybrid system can provide all the performance benefits of the existingLF solution, but with distinct advantages for a mobile device. A hybridsolution can integrate an RF ranging chip and antenna(s) into the mobiledevice. An LF chip and antenna can be substantially smaller, e.g., if itis designed to work only when the user is relatively close to or insidethe automotive (1-2 m from the center of the vehicle) as opposed to 10meters away.

In some embodiments, mobile device 610 can re-use or integrate one ormore magnetic coils in mobile device 610. Re-use of coils could becarried out by re-using coils for inductive charging or for near-fieldcommunications (NFC). Alternatively, if the mobile device does notsupport inductive charging (or NFC) or more coils are desired to providefield measurement orthogonality, additional coils can be added. Asconsumer mobile devices are space-constrained, this may limit the wiregauge, loop diameter, and number of turns in the coils.

Accordingly, a further benefit of a hybrid system can be gained byre-use of the components of an inductive (wireless) charging subsystemin the mobile device. These subsystems can include one or more inductivecoils (e.g., an LF antenna), a chip to charge the battery from thereceived magnetic field, and typically operate in the 100s of kHzfrequency range, which is similar to existing automotive LF systems. Forexample, the inductive charging coil can function in a similar manner asantenna 210 when a ranging operation is performed.

Re-use of existing wireless charging coils may cause a problem though.The number and orientation of LF antennas in the mobile device may beless than the desirable 3-D antenna configuration found in today's keyfobs, such as key fob 200. This could be overcome in various ways. Forexample, additional coils can be added to the mobile device to providefull 3-D functionality, or the automobile's existing LF antennas can beaugmented with additional antennas to generate magnetic fields in threeorthogonal directions. Such implementations can ensure that the mobiledevice can measure a strong signal regardless of the orientation of themobile device.

B. Hybrid Passive Entry System

FIG. 7 shows a mobile device having components for data collection,processing, and transfer of measurements and ancillary data according toembodiments of the present invention. Signals on LF antenna 705, whichmay correspond to multiple antennas, can be measured by LF chip 710 toprovide signal values (e.g., RSSIs). Signals on RF antenna 715, whichmay correspond to multiple antennas, can be measured by RF chip 720 toprovide signal values (e.g., time-of-flight, RSSIs, and/or angleinformation). A measurement circuitry 740 (e.g., in a programmableprocessor) can determined a distance or other distance information.Measurement circuitry 740 (or other circuitry) can include a secureelement 745 for storing and managing keys, e.g., obtaining and providingencryption and authentication keys, as is described herein.

In one embodiment, the RSSI information for an RF signal can be used toweight the time-of-flight distance. Thus, the distance determined from asignal with a low strength can be given a lower weight. The angleinformation can be determined using a spacing between two vehicleantennas and using an attitude (orientation) measurement. The directionto each of the antennas can be determined, which can be used toconstrain the location. For example, if the mobile device is in thefield-of-view of a particular antenna based on distance measurements andsignal strength (or phase), the location of the mobile device can beconstrained.

In FIG. 7 , LF RSSIs and RF distance information (e.g., time-of-flightinformation) from one or more vehicle RF and LF magnetic antennas can bemeasured on the mobile device. The measurements can then be filtered orprocessed to check on their integrity and remove outliers, e.g., bymeasurement circuitry 740, which may reside in an application processorof the mobile device. These measurements along with any requiredancillary data, such as gyrometer, accelerometer, and coarse locationdata (e.g., GPS), can be collected and then transferred back to theautomotive for precise mobile device location determination. Asexamples, sensors 750 can include gyrometer and/or accelerometer. Asexample, coarse location circuitry 760 can include GPS circuitry WiFicircuitry, or cellular circuitry. The transfer of the collectedmeasurements and ancillary data can be over any suitable wirelesscommunication system (e.g., circuitry 730 and RF antenna 725), includingWiFi, BT, UWB, or even the LF system. Such ancillary data can provideone or more other values of one or more physical properties of themobile device.

If only one magnetic coil is used, a diameter of a coil may be large,e.g., at least a ¼, ½, or nearly the longest length of the device, e.g.,about 2-5 cm. The large diameter (and potentially more windings, e.g.,4-9) can increase sensitivity for measuring magnetic flux though thecoils from the vehicles magnetic antennas. A gyrometer (e.g., one ofsensors 750) may be used in conjunction with the measurement of themagnetic coil to calibrate the signal strength for a measuredorientation. If only one device magnetic antenna is used, the signalstrength would be dependent on the orientation of the device. If thevehicle antenna is identified (e.g., using an identifier that is uniqueamong the antennas in the vehicle), then an orientation of the device(as measured by the gyrometer) can be correlated to a specificfunctional form for how distance varies against signal strength. Forinstance, one orientation (e.g., set of three angles: yaw, pitch, androll) of the mobile device would provide one set of concentric circlesof varying distance from the vehicle antenna, each circle correspondingto a different signal strength. Whereas, second orientation can have thesame concentric circles but correspond to different signal strengths, asthe different orientation would result in a different signal strengthsat a same distance from the antenna.

Measurements can be made using different orientations so as to calibratethe distance for given measurement pair (data point) of signal strengthand orientation. Not every possible combination of signal strength andorientation is needed, as interpolation or a functional fit to themeasured calibration data point can be used to fill in the gaps notcovered by the calibration data points. Accordingly, an orientation canbe measure using a sensor of the mobile device, and the orientation usedto determine a correspondence of distance between the device magneticantenna and the vehicle magnetic antenna.

In some embodiments, the LF coils may predominately be used in closeproximity to the vehicle (e.g., within 1 m or inside the vehicle), andthus the smaller magnetic coils (e.g., 0.5 cm or less) can measure asufficiently strong signal from a vehicle LF antenna when within thisrange. When farther away from the vehicle, the RF ranging system can beused. The RF signals decay slower than the magnetic fields, and 10-cmaccuracy is not needed when the device is further away from the vehicle.

A determination of whether to use the RF system or the LF system can bedetermined based on distance. For example, the RF system can begin toreceive an appreciable signal before the LF system. In this manner,location circuitry (one mobile device or in the vehicle) can selectivelyignore (or assign a low weight) to a negligible signal strength measuredby the LF system, thereby determining the relative location using the RFsystem. Then, as the RF signals indicate a closer distance and/or the LFsignals become appreciable, the LF signals can be assigned a higherweight and begin to be used. Then, at some point (e.g., based on RFand/or LF signals indicating a location within a threshold distance),the RF signal can be ignored or a weight assigned to the RF signals canbegin decreasing as the device continues to approach the vehicle. Forexample, once the device is within the vehicle, the LF system can beused exclusively, at least in some embodiments.

In some embodiments, two coils can be used, where the two coils areorthogonal or at least 45° difference in the axes of the two coils. Thediameter of one coil may be much larger than the other coil. The smallercoil may have more windings and/or thicker wire. Examples of inductanceare between 60-80 μH.

C. Dual Use

As mentioned above, a coil in a consumer device (e.g., a mobile phone orwatch) can be used for multiple purposes, one of which is for measuringmagnetic signals emitted from a vehicle antenna. Such a coil may also beused for charging the device, for communicating data via NFC, or otherpurposes. Such re-use may be implemented with any of the embodimentsthat use a magnetic antenna.

According to an embodiment, a mobile device can comprise one or moremagnetic antennas (e.g., 705 of FIG. 7 ) and strength measurementcircuitry (e.g., 710 of FIG. 7 ) coupled with the one or more magneticantennas and configured to provide a signal strength of a signal from anexternal antenna. The mobile device can also have a battery coupled withthe one or more magnetic antennas and configured to be charged viamagnetic fields interacting with the one or more magnetic antennas. Thesignal strength of the signal from the external antenna can be used indetermining a location of the mobile device.

As another example, the mobile device can also have data communicationscircuitry (e.g., for NFC) coupled with the one or more magnetic antennasand configured to communicate data with an external device. The signalstrength of the signal from the external antenna can be used indetermining a location of the mobile device.

D. Method Using Hybrid System

FIG. 8 is a flowchart of method 800 of enabling an operation by avehicle involving a mobile device according to embodiments of thepresent invention. Method 800 may be performed by mobile device thatmeasures signal values or by a vehicle that receives the signal valuesfrom the mobile device, e.g., a phone or a watch. Additionally, someembodiments can provide encryption or authentication, as well as mobiledevice/automobile discovery, e.g., as described herein.

At block 810, a first set of signal values measured using one or moredevice RF antennas of the mobile device is received. The first set ofsignal values can provide one or more first signal properties (e.g.,signal strength or time-of-flight value, such as a round trip time(RTT)) of signals from one or more vehicle RF antennas of the vehicle.The one or more first signal properties of a signal can change withrespect to a distance between a device RF antenna that received thesignal and a vehicle RF antenna that emitted the signal.

The signals from a vehicle antenna can include an identifier thatidentifies a particular antenna. In this manner, the measured signalvalues can be associated with the correct antenna. The first set ofsignal values can be measured after an identification and/orauthentication occurs between the mobile device and the vehicle. This RFmeasurement can occur at a relatively long distance from the vehicle,e.g., 15 m, 10 m, or 5 m from the vehicle. In various embodiments, theone or more RF antennas operate at a frequency in a range of 315 MHz to956 MHz, 2402 MHz to 2480 MHz (for Bluetooth), and/or 3.1 GHz to 10.6GHz (for UWB).

At block 820, a second set of signal values measured using one or moredevice magnetic antennas of the mobile device is received. The magneticantennas can operate in a low frequency range (e.g., several hundreds ofkHz, such as a range of 100 kHz to 900 kHz). The second set of signalvalues can provide one or more second signal properties of signals fromone or more vehicle magnetic antennas of the vehicle. The one or moresecond signal properties (e.g., signal strength) of a signal can changewith respect to a distance between a device magnetic antenna thatreceived the signal and a vehicle magnetic antenna that emitted thesignal. In some embodiments, the start of magnetic ranging can betriggered by RF measurements.

A set of signal values can include one signal value or multiple signalvalues. The set of signal values can include multiple signal valuesarising from one signal sent from a transmitting antenna and received bymultiple antennas. In another example, the set of signal values caninclude multiple signal values arising from multiple signals sent from atransmitting antenna and received by one or more antennas.

At block 830, a location of the mobile device is determined using thefirst set of signal values and the second set of signal values. Each ofthe signal values can correspond to a particular distance from acorresponding vehicle antenna. Based on the distances, triangulation canbe used to determine the location point that has the prescribeddistances from each of the vehicle antennas. In some embodiments, thefirst set of signal values and the second set of signal values are bothused to determine a same location at a same instance in time. In otherembodiments, the first set of signal values can be used to measure afirst location at a first time, and the second set of signal values canbe used to measure a second location at a second time, therebysatisfying the determination of a location (i.e., one or more locations)using the first set of signal values and the second set of signalvalues.

In various embodiments, a Kalman filter, particle filter, Gaussianmixture filter or a least squares technique may be used to determine thelocation. The least squares technique can function to triangulate thesignal to identify the location that best satisfies the measureddistance to all of the antennas. Measurements for different antennas canbe weighted differently in the least squares technique. Other errormetrics can be used besides the squares, e.g., the absolute value of thedifference between the measured distance and the distance of a selectedcoordinate and an antenna. Various techniques can be for solving thesystem of equations that minimizes a cost function of the error betweena selected distance (and its associated distances) and the measureddistance. For example, iterative optimization techniques can be used.The error in the measurements can be caused by noise in the signals, sothat there is not a single location that exactly provides the measureddistance to all antennas.

In some embodiments, the Kalman filter can use historical locationinformation to better inform a current location. The Kalman filter canprovide an optimal framework to provide a historical memory of thelocations. The Kalman filter can be based on typical physical motion.Different models for the Kalman filter may be used for differentphysical motion, e.g., one Kalman filter for when the user is walkingtowards the vehicle and another Kalman filter a user is within thevehicle.

The determination of the location can be performed by the mobile deviceor the vehicle. For example, the mobile device can send distanceinformation to the vehicle, which can determine the location. In someimplementations, the distance information can corresponding to atransmission time(s) of a first set of pulses and a reception time(s) ofa second set of pulses. The distance information can include timestampscorresponding to the first set of pulses in the ranging request messageand the second set of pulses in the one or more ranging responsemessages, e.g., as shown in FIG. 5 . The timestamps can be configurableto be used by a control unit of the vehicle to determine a distance ofthe mobile device from the vehicle, e.g., as described herein.

In other embodiments, the mobile device can determine the distance. Forexample, the mobile device can determine the distance using thetransmission time(s) of the first set of pulses and the receptiontime(s) of the second set of pulses, as well as positions of theantennas in the vehicle. Thus, the distance information can include thedistance.

At block 840, the location is provided (e.g., transmitted) to a controlunit of the vehicle. The location can be provided internally (e.g., whendetermined by the vehicle) or transmitted from the mobile device (e.g.,when the mobile device determines the location). In this manner, thecontrol unit can be enabled to perform a prescribed operation of thevehicle. As an example, the location can be provided from one module ofa vehicle control unit (e.g., unit 130 of FIG. 1 ) to another module,e.g., to open the doors or enable a start button. As another example,the location can be provided from the mobile device to the control unit,e.g., via an RF receiver (e.g., RF receiver 120 of FIG. 1 ).

The determination of whether a measured location is inside or outsidethe car can be made based on knowledge of the boundary of the vehicle.Whether the device is within the car can be used to determine whetherthe start button is enabled. In another example, a door or hatchback canbe prevented from closing if the device is within the vehicle. Therelationship between the boundary of the vehicle and vehicle antennascan be known by a control unit based on the design of the vehicle, e.g.,programmed into the control unit.

Accordingly, a mobile device can include circuitry used in measuringsignal values of RF signals and LF signals. According to one embodiment,a mobile device can comprise one or more RF antennas (e.g., 715 in FIG.7 ) and an RF ranging circuit (e.g., 720 in FIG. 7 ) coupled with theone or more RF antennas. The RF ranging circuit can be configured toanalyze signals from the one or more RF reception antennas and provideone or more first signal values related to a distance or an orientationof the mobile device relative to one or more RF source antennas. Themobile device can also include one or more magnetic antennas (e.g., LFantenna 705 in FIG. 7 ) and a magnetic measurement circuit (e.g., 710 inFIG. 6 ) coupled with the one or more magnetic antennas. The magneticmeasurement circuit can be configured to analyze signals from the one ormore magnetic antennas and provide one or more second signal valuesrelated to a distance of the mobile device relative to one or moremagnetic source antennas.

The mobile device can also include measurement circuitry (e.g., 740 inFIG. 7 ) that is configured to provide the one or more first signalvalues and the one or more second signal values to a location circuitryfor determining a location of the mobile device. The collectioncircuitry can be further configured to identify any outliers among theone or more first signal values and the one or more second signal valuesand exclude the outliers from providing to the location circuitry. Thelocation circuitry may be located in a device external to the mobiledevice, such as a vehicle. In such an implementation, RF antenna 725 canbe used to send the signal values.

E. Modified Vehicle

As mentioned above, the vehicle's existing LF antennas can be augmentedwith additional antennas to generate magnetic fields in three orthogonaldirections. According to one embodiment, a vehicle comprises a pluralityof sets of three orthogonal magnetic antennas. Each set of orthogonalmagnetic antennas can emit a magnetic signal that is operable to bedetected by a mobile device having a corresponding magnetic antenna fordetermining a location of the mobile device.

IV. Machine Learning

RF ranging technologies (e.g., ultra wideband (UWB)) can provide 10-cmranging accuracy, have smaller antennas, and are more resilient toman-in-the-middle attacks. However, they may be susceptible to signalattenuation, delay, and multipath due to the automotive body, nearbyobjects, and the human body. These effects can cause inaccuracies in theposition estimates, degrading the overall performance and practicalityof an RF-based system. Additionally, the mobile device may have smalleror fewer coils (magnetic antennas), which can cause weaker, fewer,and/or less accurate measurements via an LF system. Embodiments can usea machine learning model to overcome such problems.

A. Region-Based Location Determination

Instead of computing the 2-D or 3-D coordinates of the key fob, it maybe sufficient to group the locations into discrete locations of interest(e.g., inside the car and outside the car). A binary or multi-classdecision can be made based on the key fob location. Posing the problemthis way can relax the requirements of the positioning algorithm, andopens up opportunities to use a machine learning model to makedecisions, which may include using statistical hypothesis testing.

FIG. 9 shows a region-based passive entry/passive start automotivesystem according to embodiments of the present invention. FIG. 9 showsan example of grouping a subset of potential key fob locations intodiscrete regions of interest. For example, when the user is outside thelocked automobile and touches the driver-side door, the positioninglogic simply needs to make a reliable decision that the key fob is inregion 1 in order to unlock the car. Alternatively, the decision tounlock could be made if the user is in any region outside the car, i.e.,regions 1, 2, or 3. As long as the passive entry/passive start systemreceives the correct decision from the positioning algorithm, the systemwill work reliably.

Various embodiments may have more or less regions and shown in FIG. 9 .For example, there may be only two regions: inside and outside of thevehicle. As examples with more regions, a fifth region could correspondto a location outside of the four vision shown. This fifth region wouldcorrespond to the mobile device being far away from the vehicle. Intentof the user with the mobile device to approach the vehicle may beinferred via a change from the fifth region to one of the closer outsideregions, as can be done similarly when a specific distance is measured.

The four regions shown may be of different shapes than what isillustrated, e.g., region 2 may be longer such that it encompasses anentire side of the vehicle. Further, each of the regions may be brokeninto subregions. For instance, region 4 may have subregionscorresponding to different parts of the interior of the vehicle, such asfour or five different driver and passenger seats. A trunk or dashboardcould also be a region. In one embodiment, when a machine learning modelcan be used to determine when a higher level region (e.g., whetherinside or outside) and a separate model can be used to determine whichsubregion the device is within.

A machine learning (e.g., clustering, classification, or deep learning)approach to this problem is particularly valuable when the transceiversfor the car and key fob ranging are RF-based as opposed to LF-based. RFsignals are readily attenuated, delayed, reflected, and diffracted bythe automotive body, nearby objects (other cars, the ground, buildingstructures), and the human body. Note that LF signals typically do notsuffer the same impairments, or the impairments are substantiallysmaller. The signal attenuation, delays, and multipath are stochasticeffects that cause biases and noise in the range measurements.Physics-based techniques (e.g., Kalman or particle filters) that attemptto compensate for these effects are very challenging to implementreliably or have long convergence times.

B. Training

FIG. 10 shows a proposed machine learning training processing diagramaccording to embodiments of the present invention. A training module1010 of a machine learning system can receive data 1005, which caninclude distance measurements and truth data. For example, input signalvalues that correspond to distance measurements from one or moretransceivers on the vehicle can be received. As examples, the distancemeasurements can be RF, LF, or both. The truth data can correspond to adetermination made by a person as the mobile device is moved within aregion, potentially with the person in different configurations, such aswalking or standing poses. In some embodiments, such measurements can beperformed by an end user so as to calibrate for a specific care of theuser. In other embodiments, the measurements can be made by amanufacturer of the mobile device, e.g., for one or more types ofvehicles. Certain vehicles can share similar antenna configurations.

Additionally, ancillary data can be used to aid the machine learning.Examples of ancillary data include a coarse location 1030 (e.g., GPSlocation) and sensor data 1020 (e.g., accelerometer, gyrometer, etc.).This data can be used for training and providing a model 1130 inconjunction with the distance measurement data 1005. An exampleinvolving ancillary data is when the vehicle is in a home garage (e.g.,single-car garage), which can correspond to a multipath environment withlittle or no metal objects around the vehicle. Such an environment wouldbe substantially different than the multipath environment in a parkinggarage with other vehicles next to and in front of or behind the vehicleof interest. GPS can help identify which environment the vehicle is in,and the identified environment can be used as an input to the model oras a selection of which model to use. Models may be generated for eachautomotive type or for a group of automobiles

In FIG. 10 , the training of a model is shown. Distance measurements(e.g., RF or LF) can be made using a key fob, a consumer device, or atest platform from one or more automotive antennas. These measurementsalong with any required ancillary data (e.g., gyrometer, accelerometer,and/or coarse location data) can be used for machine learning trainingto produce one or more models. Additional potential machine learningfeatures can include (1) the channel impulse response between eachautomotive transceiver and the key fob and (2) ratios of the receivedpower of a first path to a second path, e.g., for multipath scenarios.

Measurements over many possible key fob locations inside and outside thecar and in various places on or near the user's body may be required forsufficient performance. Models may be generated for each automobile, ora single model may be used for multiple automobiles. The number oftraining samples can be large, and can include various paths of a userwalking towards the vehicle, with the mobile device held or carried indifferent configurations.

Examples of machine learning models include: decision trees (includinggradient boosting and random forest), support vector machines, linearregression, logistic regression, and neural networks. A single machinelearning model can be used to classify the device into one of three ormore regions (e.g., 4 regions shown in FIG. 9 ). In another embodiment,a binary decision can be made for each region as to whether the devicesin that region are not. A confidence score (probability) can bedetermined for each region having a positive decision (e.g., a distanceto a hyperplane for support vector machines or a distance from athreshold value for logistic regression). A region with the highestconfidence score can be selected as the proper region.

C. Machine Learning Passive Entry System

FIG. 11 shows an implementation of the machine learning model foridentifying which region a mobile device is located relative to avehicle according to embodiments of the present invention. The decisioncan be based on measured distance information 1115 (e.g., RF and/or LFsignal values) as obtained using antenna(s) 1105 and correspondingmeasurement circuitry 1110. Optional ancillary data can be obtained,e.g., by one or more sensors 1150 (e.g., an accelerometer or agyrometer) and coarse location circuitry 1160 (e.g., GPS) of the mobiledevice. The machine learning model 1130 can be provided to a machinelearning module 1140, which can be implemented by the mobile device orthe vehicle. For example, measured distances (as represented by signalvalues) and optional ancillary data can be transferred to the vehiclefrom the mobile device in order for the decision to be made by thevehicle. In this case, the model could be transferred to or reside onthe vehicle.

Distance information 1115 (such as time stamps, signal strengths, or anactual distance) can be measured on the mobile device using signalsreceived from one or more vehicle antennas. These measurements alongwith any required ancillary data (such as gyrometer, accelerometer, andcoarse location data) are used with the machine learning model 1130 tomake a region decision 1145. Additional input features to model 1130could be a channel impulse response and ratio of the received power forthe first path to the second path.

The channel impulse response relates to multiple signals being receivedfrom a single antenna, with each signal corresponding to a differentpath of the signal. For example, a signal can travel directly betweenthe antennas, but the signal can also reflect from various surfaces. Thechannel impulse response can be defined as a set of peaks in themeasured signal over a given time interval. The ratio of the receivedpower for a first path to a second path can measure the relative signalstrength of the direct signal (first peak) in a signal with onereflection (second peak). The first peak can be used for determining theRTT. Another feature can include a ratio of the power of the first pathrelative to the total power of the channel impulse response.

In embodiments where machine learning module 1140 is on the mobiledevice, machine learning module 1040 can send the region decision 1145to a network interface 1120 (e.g., WiFi or Bluetooth®) for transmissionvia an RF antenna 1015. The transfer of the region decision 1145 back tothe vehicle can be over any suitable wireless communication system,including WiFi, BT, or UWB. Such a machine learning approach could alsowork with conventional LF signals or as a hybrid system with LF and RFsignals.

D. Method Using Region Decision

FIG. 12 is a flowchart of a method 1200 for enabling an operation by avehicle involving a mobile device. Method 1200 can be performed by themobile device or circuitry (e.g., a programmable processor and/ordedicated circuitry) of the vehicle.

At block 1210, a set of signal values measured using one or more deviceantennas of the mobile device is received. The set of signal valuesprovide one or more signal properties of signals from a plurality ofvehicle antennas having various locations in the vehicle. For example,the vehicle antennas can be LF and/or RF antennas, as shown in FIGS. 1,3, 4, and 6 . The one or more signal properties of a signal can changewith respect to a distance between a device antenna of the mobile devicethat received the signal and a vehicle antenna that emitted the signal.In some embodiments, the set of signal values may be sent by the mobiledevice and received by the vehicle (e.g., RF receiver 120 of FIG. 1 ).In other embodiments, the set of signal values can be received by amodule of the mobile device, e.g., machine learning module 1140 of FIG.11 .

At block 1220, a machine learning model that classifies a location ofthe mobile device as being within a region of a set of regions based onthe one or more signal properties is stored. As examples, the model maybe stored as software in memory coupled to a programmable processor, orbe stored as dedicated circuitry. The set of regions can include a firstsubset of one or more regions outside the vehicle and a second subset ofone or more regions outside the vehicle. FIG. 9 provides some exampleregions.

The machine learning model can be trained using various sets of signalvalues measured at locations across the plurality of regions. Thetraining samples can be chosen to provide a representation of possiblelocations that the mobile device would be located, as well asconfigurations in orientation and placement on a user.

At block 1230, the set of signal values are provided to the machinelearning model to obtain a current classification of a particular regionwithin which the mobile device is currently located. In someimplementations, a particular signal value can be NULL or some sentinel(special) value, such as a large negative number, e.g., when ameasurement is not obtained for a particular vehicle antenna. In such asituation, another attempt may be made to obtain the signal values, oran error signal (e.g., an alert) can be provided to a user. In anotherimplementation, a last measurement from the missing antenna may be used.Alternatively, the sentinel value can be provided to the machinelearning model, which may still make a classification based on theproper signal values that were obtained.

The signal values may be obtained simultaneously, or at least within asame frame or time window. The signal values obtained within the timewindow (e.g., every second, 0.5 s, or 100 ms) can be used as a set ofsignal values. The exact time within a time window that a signal valueis received can be used for providing to the machine learning model.

In some embodiments, the classification can be performed multiple times,each potentially with an associated probability, e.g., based on adistance of a metric of the machine learning model from a cutoff valuethat separates different classifications. An average of theprobabilities can be used to determine the final classification. Inother embodiments, a majority voting procedure can be used, therebyselecting the classification that appears the most out of Nclassification measurements.

At block 1240, the particular region is provided to a control unit ofthe vehicle, thereby enabling the control unit to perform a prescribedoperation of the vehicle. Block 1240 may be performed in a similarmanner as block 840 of FIG. 8 . Results have shown at least 98% accuracyin identifying the mobile device being inside the vehicle, and at least93% accuracy in accurately identify the mobile device in an outsideregion near the vehicle.

In some embodiments, a filter (e.g., a Kalman filter) can be used forthe long-range determination of location (e.g., just using RF signals),and the machine learning model can be used for an accurate determinationof which region the mobile device is within, e.g., when the mobiledevice is closer to the vehicle. As another example, the two techniquescan be run simultaneously, and the reliability of each of the outputscan be used to dynamically select which one to use. For a Kalman filter,the signal values can be used individually when a respective measurementis obtained, and the filter can make a new determination upon each newsignal value received.

Other information can be used as input features to the machine learningmodel, e.g., a seat sensor, a door open, etc. Alternatively, such otherinformation can be used as a post-filter to confirm that nocontradictory information exists, e.g., measurements that indicate theuser is not within the car.

V. Determining Intent after Identification and Authentication

In some embodiments, the mobile device can always be listening in alow-power mode (e.g., using BTLE) for signal in a particular band. Ifthere is some level of signal in that band, the mobile device can wakeup and analyze the signal. In some implementations, the detected signalcan include an encrypted message and/or a random value that the mobiledevice is to encrypt. The mobile device can store an encryption key(symmetric or asymmetric) that can decrypt the encrypted message so asto confirm an expected value of the message, thereby authenticating thevehicle. The same or a different key can be used to encrypt the randomvalue, which can be sent to the vehicle in order for the vehicle toauthenticate the mobile device. This messaging can occur over RF (e.g.,over 400-700 MHz).

The vehicle may emit signals in response to one or more triggers, e.g.,physically interacting with a door handle, start button, trunk button,or other part of the vehicle. In another implementation, the vehicle canemit signals for a certain amount of time after use.

Accordingly, in some embodiments, the mobile device can advertise asignal (e.g., a beacon signal, as may occur in BTLE) to which thevehicle can listen and wake up. Alternatively, the vehicle can advertisea signal, and the mobile device can listen continually.

Once communication has begun, ranging can be performed, as is describedherein. Such ranging can be performed initially by RF, and in someembodiments, performed using magnetic antennas later. The switch tousing magnetic techniques can depend on a location or change in locationover time (e.g., showing an intent of a user). The intent of a user canalso be used to enable a vehicle control unity to perform an operation.To determine intent of a user, a change in the motion can be trackedover time. For example, after ranging has begun (e.g., using an RFprotocol), a change in distance can be tracked by performingtime-of-flight measurements at multiple times.

As an example, if the motion (locations over time) of the mobile deviceis in a relatively straight line to the car (e.g., within an angle of15°), then intent to use the car can be inferred. Such motion trackingmay only require an accuracy of several feet (e.g., 1 m or less). Theuse of different RF antennas can be used to triangulate the position sothat the trajectory of the motion can be determined, as opposed to justthe change distance. Such intent can allow the car to react morequickly, than requiring the user to physically interact with the carfirst. In some implementations, the motion trajectory can be used toidentify a particular part of the car that the device is approaching,e.g., the trunk, the driver's, or a particular passenger door.

Accordingly, some embodiments can determine the location of the mobiledevice at a plurality of times, thereby obtaining a plurality oflocations of the mobile device outside the vehicle. The plurality oflocations or a difference in the plurality of locations can be providedto the control unit of the vehicle, thereby enabling the control unit toperform a preparatory operation (e.g., turning on lights) of the vehiclebased on a motion of the mobile device toward the vehicle.

VI. Example Device

FIG. 13 is a block diagram of an example device 1300, which may be amobile device, in accordance with some embodiments. Device 1300generally includes computer-readable medium 1302, a processing system1304, an Input/Output (I/O) subsystem 1306, wireless circuitry 1308, andaudio circuitry 1310 including speaker 1350 and microphone 1352. Thesecomponents may be coupled by one or more communication buses or signallines 1303. Device 1300 can be any portable electronic device, includinga handheld computer, a tablet computer, a mobile phone, laptop computer,tablet device, media player, personal digital assistant (PDA), a keyfob, a car key, an access card, a multi-function device, a mobile phone,a portable gaming device, a car display unit, or the like, including acombination of two or more of these items.

It should be apparent that the architecture shown in FIG. 13 is only oneexample of an architecture for device 1300, and that device 1300 canhave more or fewer components than shown, or a different configurationof components. The various components shown in FIG. 13 can beimplemented in hardware, software, or a combination of both hardware andsoftware, including one or more signal processing and/or applicationspecific integrated circuits.

Wireless circuitry 1308 is used to send and receive information over awireless link or network to one or more other devices' conventionalcircuitry such as an antenna system, an RF transceiver, one or moreamplifiers, a tuner, one or more oscillators, a digital signalprocessor, a CODEC chipset, memory, etc. Wireless circuitry 1308 can usevarious protocols, e.g., as described herein. For example, wirelesscircuitry 1308 can have one component for one wireless protocol (e.g.,Bluetooth®) and a separate component for another wireless protocol(e.g., UWB). Different antennas can be used for the different protocols.

Wireless circuitry 1308 is coupled to processing system 1304 viaperipherals interface 1316. Interface 1316 can include conventionalcomponents for establishing and maintaining communication betweenperipherals and processing system 1304. Voice and data informationreceived by wireless circuitry 1308 (e.g., in speech recognition orvoice command applications) is sent to one or more processors 1318 viaperipherals interface 1316. One or more processors 1318 are configurableto process various data formats for one or more application programs1334 stored on medium 1302.

Peripherals interface 1316 couple the input and output peripherals ofthe device to processor 1318 and computer-readable medium 1302. One ormore processors 1318 communicate with computer-readable medium 1302 viaa controller 1320. Computer-readable medium 1302 can be any device ormedium that can store code and/or data for use by one or more processors1318. Medium 1302 can include a memory hierarchy, including cache, mainmemory and secondary memory.

Device 1300 also includes a power system 1342 for powering the varioushardware components. Power system 1342 can include a power managementsystem, one or more power sources (e.g., battery, alternating current(AC)), a recharging system, a power failure detection circuit, a powerconverter or inverter, a power status indicator (e.g., a light emittingdiode (LED)) and any other components typically associated with thegeneration, management and distribution of power in mobile devices.

In some embodiments, device 1300 includes a camera 1344. In someembodiments, device 1300 includes sensors 1346. Sensors can include oneor more accelerometers, compasses, gyrometer, pressure sensors, audiosensors, light sensors, barometers, and the like. Sensors 1346 can beused to sense location aspects, such as auditory or light signatures ofa location.

In some embodiments, device 1300 can include a GPS receiver, GlobalNavigation Satellite System (GLONASS), BeiDou, Galileo and othercombinations of devices, sometimes referred to as a GPS unit 1348. Amobile device can use a satellite navigation system, such as the GlobalPositioning System (GPS), to obtain position information, timinginformation, altitude, or other navigation information. Duringoperation, the GPS unit can receive signals from GPS satellites orbitingthe Earth. The GPS unit analyzes the signals to make a transit time anddistance estimation. The GPS unit can determine the current position(current location) of the mobile device. Based on these estimations, themobile device can determine a location fix, altitude, and/or currentspeed. A location fix can be geographical coordinates such aslatitudinal and longitudinal information.

One or more processors 1318 run various software components stored inmedium 1302 to perform various functions for device 1300. In someembodiments, the software components include an operating system 1322, acommunication module (or set of instructions) 1324, a location module(or set of instructions) 1326, a distance module 1328 (e.g., includingsoftware for analyzing or controlling an RF ranging chip or an LF chip,possibly including a machine learning model), and other applications (orset of instructions) 1334. Distance module 1328 can send/receive rangingmessages to/from an antenna, e.g., connected to wireless circuitry 1308.The messages can be used for various purposes, e.g., to identify asending antenna of a vehicle, determine timestamps of messages (e.g.,for sending to the vehicle), and potentially to determine a distance ofmobile device 1300 from the vehicle. As an example, distance module 1328may include machine learning module 1140.

Operating system 1322 can be any suitable operating system, includingiOS, Mac OS, Darwin, RTXC, LINUX, UNIX, OS X, WINDOWS, or an embeddedoperating system such as VxWorks. The operating system can includevarious procedures, sets of instructions, software components and/ordrivers for controlling and managing general system tasks (e.g., memorymanagement, storage device control, power management, etc.) andfacilitates communication between various hardware and softwarecomponents.

Communication module 1324 facilitates communication with other devicesover one or more external ports 1336 or via wireless circuitry 1308 andincludes various software components for handling data received fromwireless circuitry 1308 and/or external port 1336. External port 1336(e.g., USB, FireWire, Lightning connector, 60-pin connector, etc.) isadapted for coupling directly to other devices or indirectly over anetwork (e.g., the Internet, wireless LAN, etc.).

Location/motion module 1326 can assist in determining the currentposition (e.g., coordinates or other geographic location identifier) andmotion of device 1300. Location/motion module can include a machinelearning module, as well as relate to more standard locationfunctionality. Modern positioning systems include satellite basedpositioning systems, such as Global Positioning System (GPS), cellularnetwork positioning based on “cell IDs,” and Wi-Fi positioningtechnology based on a Wi-Fi networks. GPS also relies on the visibilityof multiple satellites to determine a position estimate, which may notbe visible (or have weak signals) indoors or in “urban canyons.” In someembodiments, location/motion module 1326 receives data from GPS unit1348 and analyzes the signals to determine the current position of themobile device. In some embodiments, location/motion module 1326 candetermine a current location using Wi-Fi or cellular locationtechnology. For example, the location of the mobile device can beestimated using knowledge of nearby cell sites and/or Wi-Fi accesspoints with knowledge also of their locations. Information identifyingthe Wi-Fi or cellular transmitter is received at wireless circuitry 1308and is passed to location/motion module 1326. In some embodiments, thelocation module receives the one or more transmitter IDs. In someembodiments, a sequence of transmitter IDs can be compared with areference database (e.g., Cell ID database, Wi-Fi reference database)that maps or correlates the transmitter IDs to position coordinates ofcorresponding transmitters, and computes estimated position coordinatesfor device 1300 based on the position coordinates of the correspondingtransmitters. Regardless of the specific location technology used,location/motion module 1326 can receive information from which alocation fix can be derived, interprets that information, and returnslocation information, such as geographic coordinates,latitude/longitude, or other location fix data.

The one or more applications 1334 on the mobile device can include anyapplications installed on the device 1300, including without limitation,a browser, address book, contact list, email, instant messaging, wordprocessing, keyboard emulation, widgets, JAVA-enabled applications,encryption, digital rights management, voice recognition, voicereplication, a music player (which plays back recorded music stored inone or more files, such as MP3 or AAC files), etc.

There may be other modules or sets of instructions (not shown), such asa graphics module, a time module, etc. For example, the graphics modulecan include various conventional software components for rendering,animating and displaying graphical objects (including without limitationtext, web pages, icons, digital images, animations and the like) on adisplay surface. In another example, a timer module can be a softwaretimer. The timer module can also be implemented in hardware. The timemodule can maintain various timers for any number of events.

The I/O subsystem 1306 can be coupled to a display system (not shown),which can be a touch-sensitive display. The display displays visualoutput to the user in a GUI. The visual output can include text,graphics, video, and any combination thereof. Some or all of the visualoutput can correspond to user-interface objects. A display can use LED(light emitting diode), LCD (liquid crystal display) technology, or LPD(light emitting polymer display) technology, although other displaytechnologies can be used in other embodiments.

In some embodiments, I/O subsystem 1306 can include a display and userinput devices such as a keyboard, mouse, and/or track pad. In someembodiments, I/O subsystem 1306 can include a touch-sensitive display. Atouch-sensitive display can also accept input from the user based onhaptic and/or tactile contact. In some embodiments, a touch-sensitivedisplay forms a touch-sensitive surface that accepts user input. Thetouch-sensitive display/surface (along with any associated modulesand/or sets of instructions in medium 1302) detects contact (and anymovement or release of the contact) on the touch-sensitive display andconverts the detected contact into interaction with user-interfaceobjects, such as one or more soft keys, that are displayed on the touchscreen when the contact occurs. In some embodiments, a point of contactbetween the touch-sensitive display and the user corresponds to one ormore digits of the user. The user can make contact with thetouch-sensitive display using any suitable object or appendage, such asa stylus, pen, finger, and so forth. A touch-sensitive display surfacecan detect contact and any movement or release thereof using anysuitable touch sensitivity technologies, including capacitive,resistive, infrared, and surface acoustic wave technologies, as well asother proximity sensor arrays or other elements for determining one ormore points of contact with the touch-sensitive display.

Further, the I/O subsystem can be coupled to one or more other physicalcontrol devices (not shown), such as pushbuttons, keys, switches, rockerbuttons, dials, slider switches, sticks, LEDs, etc., for controlling orperforming various functions, such as power control, speaker volumecontrol, ring tone loudness, keyboard input, scrolling, hold, menu,screen lock, clearing and ending communications and the like. In someembodiments, in addition to the touch screen, device 1300 can include atouchpad (not shown) for activating or deactivating particularfunctions. In some embodiments, the touchpad is a touch-sensitive areaof the device that, unlike the touch screen, does not display visualoutput. The touchpad can be a touch-sensitive surface that is separatefrom the touch-sensitive display or an extension of the touch-sensitivesurface formed by the touch-sensitive display.

In some embodiments, some or all of the operations described herein canbe performed using an application executing on the user's device.Circuits, logic modules, processors, and/or other components may beconfigured to perform various operations described herein. Those skilledin the art will appreciate that, depending on implementation, suchconfiguration can be accomplished through design, setup,interconnection, and/or programming of the particular components andthat, again depending on implementation, a configured component might ormight not be reconfigurable for a different operation. For example, aprogrammable processor can be configured by providing suitableexecutable code; a dedicated logic circuit can be configured by suitablyconnecting logic gates and other circuit elements; and so on.

Any of the software components or functions described in thisapplication may be implemented as software code to be executed by aprocessor using any suitable computer language such as, for example,Java, C, C++, C#, Objective-C, Swift, or scripting language such as Perlor Python using, for example, conventional or object-orientedtechniques. The software code may be stored as a series of instructionsor commands on a computer readable medium for storage and/ortransmission. A suitable non-transitory computer readable medium caninclude random access memory (RAM), a read only memory (ROM), a magneticmedium such as a hard-drive or a floppy disk, or an optical medium suchas a compact disk (CD) or DVD (digital versatile disk), flash memory,and the like. The computer readable medium may be any combination ofsuch storage or transmission devices.

Computer programs incorporating various features of the embodiments maybe encoded on various computer readable storage media; suitable mediainclude magnetic disk or tape, optical storage media such as compactdisk (CD) or DVD (digital versatile disk), flash memory, and the like.Computer readable storage media encoded with the program code may bepackaged with a compatible device or provided separately from otherdevices. In addition program code may be encoded and transmitted viawired optical, and/or wireless networks conforming to a variety ofprotocols, including the Internet, thereby allowing distribution, e.g.,via Internet download. Any such computer readable medium may reside onor within a single computer product (e.g. a solid state drive, a harddrive, a CD, or an entire computer system), and may be present on orwithin different computer products within a system or network. Acomputer system may include a monitor, printer, or other suitabledisplay for providing any of the results mentioned herein to a user.

Although the invention has been described with respect to specificembodiments, it will be appreciated that the invention is intended tocover all modifications and equivalents within the scope of thefollowing claims.

A recitation of “a”, “an” or “the” is intended to mean “one or more”unless specifically indicated to the contrary. The use of “or” isintended to mean an “inclusive or,” and not an “exclusive or” unlessspecifically indicated to the contrary. Reference to a “first” componentdoes not necessarily require that a second component be provided.Moreover reference to a “first” or a “second” component does not limitthe referenced component to a particular location unless expresslystated. The term “based on” is intended to mean “based at least in parton.”

What is claimed is:
 1. A method performed by a mobile device, the methodcomprising: receiving a first set of signal values measured using one ormore first radiofrequency (RF) antennas of the mobile device, the firstset of signal values providing one or more first signal properties ofsignals in a first frequency range emitted from one or more second RFantennas of a control unit connected to a door, wherein the one or morefirst signal properties of a signal change with respect to a distancebetween a first RF antenna that received the signal and a second RFantenna that emitted the signal; receiving a second set of signal valuesmeasured using one or more first magnetic antennas of the mobile device,the second set of signal values providing one or more second signalproperties of signals in a second frequency range lower than the firstfrequency range emitted from one or more second magnetic antennas of thecontrol unit, wherein the one or more second signal properties of asignal change with respect to a distance between a first magneticantenna that received the signal and a second magnetic antenna thatemitted the signal; determining a location of the mobile device relativeto the control unit using the one or more first signal properties of thefirst set of signal values and the one or more second signal propertiesof the second set of signal values that change with respect to arelative distance between the mobile device and the control unit; andproviding the location of the mobile device relative to the controlunit, thereby enabling the control unit to perform a prescribedoperation for the door based on the location of the mobile devicerelative to the control unit.
 2. The method of claim 1, furthercomprising: receiving an orientation measured using a sensor of themobile device; and using the orientation to determine a correspondenceof distance between a respective first magnetic antenna and a respectivesecond magnetic antenna.
 3. The method of claim 1, wherein the locationof the mobile device is determined using the first set of signal valuesmeasured using the one or more first RF antennas at a first time whenthe mobile device is outside a predefined distance of the control unit,and wherein the location of the mobile device is determined using thesecond set of signal values measured using the one or more firstmagnetic antennas at a second time when the mobile device is inside thepredefined distance of the control unit.
 4. The method of claim 1,wherein determining the location of the mobile device relative to thecontrol unit includes: storing a model that determines the location ofthe mobile device relative to the control unit based on the one or morefirst signal properties and the one or more second signal properties;and providing the first set of signal values and the second set ofsignal values to the model to obtain the location of the mobile devicerelative to the control unit.
 5. The method of claim 4, wherein themodel is a machine learning model that classifies a location of themobile device relative to the control unit as being within a region of aset of pre-defined regions based on the one or more first signalproperties and the one or more second signal properties, the set ofpre-defined regions including a first subset of one or more regionsoutside a predefined distance of the control unit and a second subset ofone or more regions outside the predefined distance of the control unit,the machine learning model being trained using various sets of signalvalues measured at locations across the set of pre-defined regions; andwherein the location of the mobile device relative to the control unitcorresponds to a current classification of a particular region withinwhich the mobile device is currently located.
 6. The method of claim 1,wherein the one or more first RF antennas operate within a range of 3.1GHz to 10.6 GHz, and wherein the one or more first magnetic antennasoperate within a range of 100 kHz to 900 kHz.
 7. A non-transitorycomputer-readable medium storing a plurality of instructions that, whenexecuted by one or more processors of a mobile device, cause the one ormore processors to perform operations comprising: receiving a first setof signal values measured using one or more first radiofrequency (RF)antennas of the mobile device, the first set of signal values providingone or more first signal properties of signals in a first frequencyrange emitted from one or more second RF antennas of a control unitconnected to a door, wherein the one or more first signal properties ofa signal change with respect to a distance between a first RF antennathat received the signal and a second RF antenna that emitted thesignal; receiving a second set of signal values measured using one ormore first magnetic antennas of the mobile device, the second set ofsignal values providing one or more second signal properties of signalsin a second frequency range lower than the first frequency range emittedfrom one or more second magnetic antennas of the control unit, whereinthe one or more second signal properties of a signal change with respectto a distance between a first magnetic antenna that received the signaland a second magnetic antenna that emitted the signal; determining alocation of the mobile device relative to the control unit using the oneor more first signal properties of the first set of signal values andthe one or more second signal properties of the second set of signalvalues that change with respect to a relative distance between themobile device and the control unit; and providing the location of themobile device relative to the control unit, thereby enabling the controlunit to perform a prescribed operation for the door based on thelocation of the mobile device relative to the control unit.
 8. Thenon-transitory computer-readable medium of claim 7, wherein theplurality of instructions that, when executed by the one or moreprocessors of the mobile device, cause the one or more processors tofurther perform operations comprising: receiving an orientation measuredusing a sensor of the mobile device; and using the orientation todetermine a correspondence of distance between a respective firstmagnetic antenna and a respective second magnetic antenna.
 9. Thenon-transitory computer-readable medium of claim 7, wherein the locationof the mobile device is determined using the first set of signal valuesmeasured using the one or more first RF antennas at a first time whenthe mobile device is outside a predefined distance of the control unit,and wherein the location of the mobile device is determined using thesecond set of signal values measured using the one or more firstmagnetic antennas at a second time when the mobile device is inside thepredefined distance of the control unit.
 10. The non-transitorycomputer-readable medium of claim 7, wherein determining the location ofthe mobile device relative to the control unit includes: storing a modelthat determines the location of the mobile device relative to thecontrol unit based on the one or more first signal properties and theone or more second signal properties; and providing the first set ofsignal values and the second set of signal values to the model to obtainthe location of the mobile device relative to the control unit.
 11. Thenon-transitory computer-readable medium of claim 10, wherein the modelis a machine learning model that classifies a location of the mobiledevice relative to the control unit as being within a region of a set ofpre-defined regions based on the one or more first signal properties andthe one or more second signal properties, the set of pre-defined regionsincluding a first subset of one or more regions outside a predefineddistance of the control unit and a second subset of one or more regionsoutside the predefined distance of the control unit, the machinelearning model being trained using various sets of signal valuesmeasured at locations across the set of pre-defined regions; and whereinthe location of the mobile device relative to the control unitcorresponds to a current classification of a particular region withinwhich the mobile device is currently located.
 12. The non-transitorycomputer-readable medium of claim 7, wherein the one or more first RFantennas operate within a range of 3.1 GHz to 10.6 GHz, and wherein theone or more first magnetic antennas operate within a range of 100 kHz to900 kHz.
 13. The non-transitory computer-readable medium of claim 7,wherein the mobile device comprises collection circuitry configured toprovide the one or more first signal values and the one or more secondsignal values to a location circuitry for determining a location of themobile device relative to the control unit.
 14. A mobile devicecomprising: one or more radiofrequency (RF) reception antennas; an RFranging circuit coupled with the one or more RF reception antennas, theRF ranging circuit configured to: analyze signals in a first frequencyrange from the one or more RF reception antennas; and provide one ormore first signal values related to a distance or an orientation of themobile device relative to one or more RF source antennas associated witha control unit connected to a door; one or more magnetic antennas; and amagnetic measurement circuit coupled with the one or more magneticantennas, the magnetic measurement circuit configured to: analyzesignals in a second frequency range lower than the first frequency rangefrom the one or more magnetic antennas; and provide one or more secondsignal values related to a distance of the mobile device relative to oneor more magnetic source antennas associated with the control unit. 15.The mobile device of claim 14, further comprising: collection circuitryconfigured to provide the one or more first signal values and the one ormore second signal values to a location circuitry for determining alocation of the mobile device relative to the control unit.
 16. Themobile device of claim 15, wherein the location circuitry is located ina device external to the mobile device.
 17. The mobile device of claim16, wherein the external device is in control unit.
 18. The mobiledevice of claim 17, wherein the location circuitry is configured to:store a machine learning model that classifies a location of the mobiledevice relative to the control unit as being within a region of a set ofpre-defined regions based on the one or more first signal values, theone or more second signal values, or both, wherein the set ofpre-defined regions including a first subset of one or more regionsoutside the a predefined distance from the control unit and a secondsubset of one or more regions outside the predefined distance from thecontrol unit, the machine learning model being trained using varioussets of signal values measured at locations across the set ofpre-defined regions; and provide the set of signal values to the machinelearning model to obtain a current classification of a particular regionwithin which the mobile device is currently located.
 19. The mobiledevice of claim 18, further comprising: data communication circuitryconfigured to provide the particular region to the control unit, therebyenabling the control unit to perform a prescribed operation associatedwith the door.
 20. The mobile device of claim 15, wherein the collectioncircuitry is further configured to: identify any outliers among the oneor more first signal values and the one or more second signal values;and exclude the outliers from providing to the location circuitry.